I would like to know which analytical and/or deep learning algorithms Slicer uses to denoise the forward projection X-rays (also known as sinograms). These X-rays exhibit a host of noise profiles, such as beam hardening, streaking artifacts, and aliasing. How does Slicer lower these noise profiles? Thanks.